Yifan Xue
Papers
1
Total Citations
4
H-Index
1
About
Yifan Xue is a rising researcher in marine robotics and data-driven dynamical systems, with a focus on robust control under unpredictable ocean environments. Their key research areas include Koopman operator theory, online learning for nonlinear dynamics, and autonomous marine vehicle steering. Xue’s major contribution is the development of the Online Memory Koopman Learning (OM-Koop) framework, which enables rapid, accurate online learning of steering dynamics for marine robots amidst complex disturbances—a critical advancement for real-time autonomous maneuvering. This work, published in 2025, has already garnered 4 citations, signaling early impact in the field. Xue’s research bridges the gap between theoretical dynamical systems and practical robotics, offering a hybrid approach that enhances adaptability and memory retention in learning models. Their work is notable for addressing the long-standing challenge of balancing online learning speed with model accuracy in noisy, real-world settings. As a young scholar, Xue’s innovative framework holds promise for advancing autonomous marine navigation and broader applications in adaptive control.
Research Focus
Key Achievements
Top Papers
- 1